Many attempts have been made to provide means for restoring deteriorated digitized frames, and an example of some of those attempts are disclosed in the following prior art patents.
U.S. Pat. No. 5,266,805 by Edgar, recites a system and method for image recovery to compensate for effects of a recording medium such as film on image data retrieved therefrom.
U.S. Pat. No. 5,355,421 to Koyama recites a method for identifying and removing noise from digitized images includes the steps for judging whether or not a group of black pixels represents a noise by analyzing the number of pixels in the group, the degree of flattening of the group and the curvature of the region.
U.S. Pat. No. 5,850,471 to Brett recites a high-definition digital video processing system for correcting video color and other attributes, such as pixel location and sharpness.
U.S. Pat. No. 6,035,072 to Read, recites the mapping defects of such as dirt, dust, scratches, blemishes, pits, or defective elements or pixels in a CCD, scanner, photocopier, or image acquiring device, dynamically detected by processing a plurality of images via a computer.
U.S. Pat. No. 6,160,923 to Lawton, et al. recites a user directed dust and compact anomaly remover from digital images which is a technique of editing a digital image for the automatic removal of blotchy areas.
U.S. Pat. No. 6,233,364 to Krainiouk, et al. is for a method and system for detecting and tagging dust and scratches in a digital image, which is a system for identifying and tagging anomalies, such as images of dust and scratches in a digital image so that they can be removed from the image.
U.S. Pat. No. 6,266,054 to Lawton, et al. recites the automated removal of narrow, elongated distortions from a digital image, by using an apparatus including a method of digital image processing which allows a user to remove narrow, elongated areas of image distortion from a digitized image.
U.S. Pat. No. 6,728,005 to Jia, et al. recites a method for the automatic removal of image artifacts that includes the steps of comparing scanned image data pertaining to regions where it is possible for image artifacts to be present to idealized image artifact data, determining whether image artifacts or partial image artifacts are present in the known regions, excluding such regions or portions of them as appropriate from a scannable area, and generating an image from the elements of the scanned image data pertaining only to the portions of the scannable area for which no image artifacts are determined to be present.
U.S. Pat. No. 6,931,160 to Gindele, et al. recites a method of spatially filtering digital image that includes receiving a source digital image including pixels corresponding to one or more different colors; selecting a pixel of interest in the source digital image; calculating two or more noise free pixel estimates for the pixel of interest using pixel values sampled in a local region about the pixel of interest; selecting a final noise free pixel estimate for the pixel of interest from the noise free pixel estimates; and repeating for other pixels in the source digital image to provide a spatially filtered digital image.
U.S. Pat. No. 7,020,346 to Dupont, et al., recites a method for the removal of scratches from digital images that provides for a method which restores a digitized image or a series of digitized images automatically, by eliminating straight or virtually straight scratches in the images.
Finally, U.S. Pat. No. 6,307,979 to Kondo, et al. is for a classified adaptive error recovery method and apparatus and article of manufacture for restoring a deteriorated signal to an undeteriorated signal. A deteriorated signal consists of a plurality of deteriorated and undeteriorated data points. For each deteriorated data point, a plurality of class types is created based upon characteristics of the area containing the deteriorated data point.
However, none of the citations hereinabove is capable of automatically restoring still frames, digital film frames, and video frames without adding new artifacts.